fix: clean up inadvertent change in tf_t5

This was the beginnings of an attempt to address the test failure on
this layer, and instead I backed out of making this layer
keras-serializable at all ... so it was a mistake to commit this.

src/transformers/modeling_tf_t5.py

@@ -383,21 +383,14 @@ class TFT5MainLayer(tf.keras.layers.Layer):
 
     def call(
         self,
-        inputs,
+        hidden_states,
         attention_mask=None,
         encoder_hidden_states=None,
         encoder_attention_mask=None,
         head_mask=None,
         training=False,
     ):
-        if isinstance(inputs, (tuple, list)):
-            hidden_states = inputs[0]
-            assert len(inputs) <= 1, "Too many inputs."
-        elif isinstance(inputs, dict):
-            hidden_states = inputs["hidden_states"]
-            assert len(inputs) <= 1, "Too many inputs."
-        else:
-            hidden_states = inputs
+
         batch_size, seq_length = shape_list(hidden_states)[:2]
         if attention_mask is None:
             attention_mask = tf.fill((batch_size, seq_length), 1)